Where Do People Tell Stories Online? Story Detection Across Online Communities (2024.acl-long)
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| Challenge: | Story detection in online communities is a challenging task as stories are scattered across communities and interwoven with non-storytelling spans within a single text. |
| Approach: | They propose a toolkit to detect stories in online communities using an annotated reddit dataset and a codebook adapted to social media context. |
| Outcome: | The proposed toolkit includes an annotation-rich dataset of 502 Reddit posts and comments . it also includes a codebook adapted to the social media context and models to predict storytelling at document and span levels. |
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| Challenge: | Identifying stories in social media texts provides a lens through which we can study how individuals and communities process and communicate experiences. |
| Approach: | They construct a taxonomy of crowd workers’ varied and nuanced perceptions of storytelling by open-coding their free-text rationales. |
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“Let Your Characters Tell Their Story”: A Dataset for Character-Centric Narrative Understanding (2021.findings-emnlp)
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| Challenge: | Existing studies on character-centric understanding of narratives focus on understanding the characters in the narrative, but these studies are limited to understanding only certain aspects of characters. |
| Approach: | They propose a dataset of literary pieces and their summaries paired with descriptions of characters that appear in them that are used to facilitate character-centric narrative understanding. |
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Exploring Text Recombination for Automatic Narrative Level Detection (2022.lrec-1)
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| Challenge: | Existing annotation workflows do not scale well to the annotation of complex narrative phenomena. |
| Approach: | They propose a workflow for narrative level detection that includes operationalization and a model . they propose generating training data synthetically to improve the prediction results . |
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Story Embeddings — Narrative-Focused Representations of Fictional Stories (2024.emnlp-main)
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| Challenge: | Existing approaches to model fictional narratives have focused on the aspect of "what" rather than "how" they are being told. |
| Approach: | They propose a model that embeds stories such that similar stories will result in similar embeddings. |
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Stories and Personal Experiences in the COVID-19 Discourse (2024.lrec-main)
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| Challenge: | 'storytelling' is a human strategy to use personal experiences to back-up one's position in debates about controversial topics. |
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A Structured Clustering Approach for Inducing Media Narratives (2026.acl-long)
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| Challenge: | Existing approaches to modeling media narratives miss subtle narrative patterns through coarse-grained analysis or require domain-specific taxonomies that limit scalability. |
| Approach: | They propose a framework for inducing rich narrative schemas by jointly modeling events and characters via structured clustering. |
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Using RL to Identify Divisive Perspectives Improves LLMs Abilities to Identify Communities on Social Media (2024.findings-emnlp)
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| Challenge: | Experimental results show improvements on Reddit and Twitter data . |
| Approach: | They propose to take advantage of Large Language Models (LLMs) to better identify user communities. |
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My side, your side and the evidence: Discovering aligned actor groups and the narratives they weave (2023.acl-long)
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| Challenge: | Identify distinct sets of aligned story actors responsible for sustaining issue-specific narratives . authors propose a novel two-step graph-based framework that identifies alignments between actors . |
| Approach: | They propose a proxy task to identify the distinct sets of aligned story actors . they propose identifying alignments between actors and extracting alignes using TAMPA . |
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Tell Me Again! a Large-Scale Dataset of Multiple Summaries for the Same Story (2024.lrec-main)
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| Challenge: | Existing approaches to represent narratives on short-form texts are limited as narrative semantics are an open class. |
| Approach: | They propose to use Wikipedia summaries as a proxy for entire stories or for analysis of the summary itself. |
| Outcome: | The proposed dataset contains 96,831 individual summaries across 29,505 stories. |
Beyond Detection: A Defend-and-Summarize Strategy for Robust and Interpretable Rumor Analysis on Social Media (2023.emnlp-main)
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| Challenge: | Existing detection models for rumors detection are poor interpretability and lack the textual content to detect rumors. |
| Approach: | They propose a framework that analyzes the textual content and propagation paths of rumors on social media and provides multi-perspective prediction explanations. |
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